Fall 2017 Workshops

September 25, 2017 (Monday) 4:20 - 5:50 PM

Peter Molk

  • Assistant Professor of Law, Willamette University College of Law (Salem, OR)

Location: 

Case Lounge (Jerome Greene Hall room 701).

Topic: 

Playing with Fire? Testing Moral Hazard in Homeowners Insurance Valued Policies

Abstract:  

Insurance policy design and regulation continually grapples with moral hazard concerns. Yet these concerns rest largely on theory-based assumptions about how rational economic actors will respond to financial incentives. Advances in behavioral economics call these assumptions into question.

This Article conducts an empirical test of moral hazard in homeowners insurance markets. Eighteen states’ “valued policy” laws require more generous compensation by insurers for certain total house losses. I test the moral hazard prediction that fire rates will consequently be higher in these states than in others. Using a private insurance database on the cause of loss for over four million residential insurance claims from 2002 through 2011, I find that, surprisingly, loss rates are significantly lower in valued policy states, not higher. I also use Louisiana’s unexpected elimination of these laws as an additional means to assess the laws’ effects. As before, fire rates are significantly higher when economic incentives appear lower.

These results are inconsistent with standard moral hazard predictions, but I demonstrate how they are consistent with a broader conceptualization of moral hazard theory. First, the results show the importance of recognizing policyholders’ responsiveness to irrelevant factors that they nevertheless believe will affect their insurance payments, like housing prices, rather than the low-salience economic factors that truly determine these payments, like valued policy laws. Second, the results show how focusing exclusively on policyholder behavior misses how other actors, like insurance companies, also adjust to mitigate or even entirely eliminate moral hazard considerations.


September 28, 2017 (Thursday) 12:00 PM (also a faculty lunch)

Andrew Verstein

  • Associate Professor of Law, Wake Forest University College of Law (Winston Salem, NC)
  • Visiting Associate Professor of Law, University of Chicago Law School (Chicago, IL)

Location: 

Case Lounge (Jerome Greene Hall room 701).

Topic:  

Insider Tainting: Strategic Tipping of Material Non-Public Information

Abstract: 

Insider trading law is meant to be a shield, protecting the market and investors from unscrupulous traders, but it can also be a sword. Insofar as we penalize trading on the basis of material, non-public information, it becomes possible to share information strategically in order to disable or constrain innocent investors. A hostile takeover can be averted, or a bidding war curtailed, because recipients of such information must then refrain from trading. This Article offers the first general account of “insider tainting,” an increasingly pervasive phenomenon of weaponizing insider trading law.


October 9, 2017 (Monday) 4:20 - 5:50 PM

Frank Giaoui

  • Visiting Scholar & JSD Candidate, Columbia Law School (New York, NY)
  • Research Scholar at Columbia Business School
  • PhD Candidate at Sorbonne Law School (Paris, France)
  • Managing Partner of Hera Finance corporate advisory
  • ESSEC Business School graduate and former visiting professor.

Location: 

Case Lounge (Jerome Greene Hall room 701).

Topic:  

Valuation of damages as a remedy for contract breach: A legal innovation from empirical research on American common law, French civil law and International private law

Abstract:  

The assessment of economic harm and compensatory damages for contract breach has traditionally navigated between two practical difficulties: judicial uncertainty and technical complexity. Judicial uncertainty is particularly high when objective data are missing. And when data exist, financial and statistical methodologies are too complex and costly for the overwhelming majority of cases. This leads to inefficient bargaining, unnecessary litigations and/or unpredictable/arbitrary judicial decisions.

Hence there is a need for alternative methods that are both objective/predictable and simpler/cheaper than current quantitative methods. One of those methods would be to develop damages scales for certain types of economic loss as they exist for bodily injury. A good way to start is to study case law and to survey as many rulings as possible that can be used as precedents for different classes of economic damages.

We have selected three types of business situations where we think the use of simple quantitative methods is most relevant to assess economic loss due to contract breach. For each of thos situations we successively designed hypothesis of the findings we were looking for, developed a template with fact specific criteria, searched and identified recent and relevant cases and built a database with those cases. We then used the database to validate or amend the initial hypothesis, to identify patterns or correlations and when relevant to suggest damage ranges or scales.

We show that reference ranges can be observed from relevant precedents of contract damages. We claim such ranges may benefit the academics debate and the parties’ attorneys contract drafting or pre-litigation settlement. We suggest continuous empirical research on certain types of contracts damages could eventually lead to shared and updated compensatory scales which courts and judges would use as tools to assist their rulings.


October 23, 2017 (Monday) 4:20 - 5:50 PM

Greg Sidak

  • founder, Criterion Economics (Washington, DC)

Location: 

Case Lounge (Jerome Greene Hall room 701).

Topic: 

Hedonic Prices and Patent Royalties

Abstract: 

A hedonic model explains a good’s price in terms of its characteristics.  In this article, we use hedonic prices to estimate the permissible range for a reasonable royalty for a standard-essential patent (SEP) subject to its owner’s commitment to offer to license the patent on reasonable and nondiscriminatory (RAND) terms. Our methodology is equally applicable to the calculation of fair, reasonable, and nondiscriminatory (FRAND) royalties for SEPs. The immediate purpose of our analysis is to determine whether, as a matter of contract law, a particular offer that the SEP holder has made has discharged its obligation to its standard-setting organization (SSO) to make an offer to license its SEPs on RAND or FRAND terms to a third party seeking to implement the standard. However, if asked or required to set a specific RAND or FRAND rate for a specific portfolio of SEPs, a court or arbitral panel could take our analysis one step further, by determining where within the RAND or FRAND bargaining range a bilaterally negotiated royalty between the parties would most likely fall.

 


November 6, 2017 (Monday) 4:20 - 5:50 PM

Lee Alston

  • Director, Vincent and Elinor Ostrom Workshop in Political Theory and Policy Analysis
  • Affliated Professor of Law, Indiana University, Maurer School of Law (Bloomington, IN)

Location: 

Case Lounge (Jerome Greene Hall room 701).

Topic: 

Institutional and Organizational Analysis: Concepts and Applications (Cambridge University Press, forthcoming):

Abstract:  

Developmental Trajectories: Institutional Deepening and Critical Transitions
Beliefs shape the choices of institutions. Beliefs are generally stable, but shocks that cause sufficiently unexpected economic and political outcomes make beliefs malleable and create a window of opportunity for changing beliefs. Within these windows of opportunity, leadership can play a role in shaping a new belief among the dominant organizations that in turn generates new institutions and over time a possible transition to a new developmental trajectory.


November 20, 2017 (Monday) 4:20 - 5:50 PM

Justin McCrary

  • Professor of Law
  • Director, Social Science Data Laboratory, University of California Berkeley School of Law (Berkeley, CA)

Location: 

Case Lounge (Jerome Greene Hall room 701).

Topic:  

Unmarked? Criminal Record Clearing and Employment Outcomes

Abstract:  

An estimated one in three American adults has a criminal record. While some records are for serious offenses, most are for arrests or relatively lowlevel misdemeanors. In an era of heightened security concerns, easily available data and increased criminal background checks, these records act as a substantial barrier to gainful employment and other opportunities. Harvard sociologist Devah Pager describes people with criminal records as “marked” with a negative job credential.

In response to this problem, lawyers have launched unmarking programs to help people take advantage of legal record clearing remedies. We study a random sample of participants in one such program to analyze the impact of the record clearing intervention on employment outcomes. Using methods to control for selection bias and the effects of changes in the economy in our data, we find evidence that: (1) the record clearing intervention boosts participants’ employment rates and average real earnings, and (2) people seek record clearing remedies after a period of suppressed earnings.

More research needs to be done to understand the durability of the positive impact and its effects in different local settings and labor markets, but these findings suggest that the record clearing intervention makes a meaningful difference in employment outcomes for people with criminal records. The findings also suggest the importance of early intervention to increase opportunities for people with criminal records. Such interventions might include more legal services, but they might also include record clearing by operation of law or another mechanism that does not put the onus of unmarking on the person with a criminal record.


December 4, 2017 (Monday) 4:20 - 5:50 PM

Sonja Starr

  • Professor of Law
  • Codirector, Empirical Legal Studies Center, University of Michigan Law School (Ann Arbor, MI)

Location: 

Case Lounge (Jerome Greene Hall room 701).

Topic:  

Do Employers’ Neighborhoods Predict Racial Discrimination?

Abstract: 

This paper uses evidence from a large field experiment to explore whether the racial composition of employers’ neighborhoods, as well as other neighborhood and business characteristics, predicts racially discriminatory employment decisions. Over 15,000 fictitious job applications were sent, in otherwise-similar black and white pairs, to low-skill job postings distributed throughout New Jersey and New York City. Overall, white applicants received 23% more callbacks than equivalent black applicants. The white advantage was much larger in whiter and less black neighborhoods. We interpret this pattern to suggest some form of in-group preference and/or irrational stereotypes; the pattern cannot readily be explained by “rational” statistical discrimination. In prior work on Ban-the-Box laws, we showed that when employers lack access to criminal records they appear to make exaggerated negative assumptions about the likely criminality of black applicants. We now show that this effect too was driven by employers in less black neighborhoods, and conversely that this apparent stereotyping pattern can explain some (but not most) of the effect of neighborhood composition on the black/white callback gap.

Real-world black applicants are presumably more likely to apply to jobs in black neighborhoods (and white applicants to jobs in white neighborhoods) because they are more likely to live nearby. Through simulations that reweight our results geographically to mirror a real-world population distribution by race, we show that this geographic self-sorting will likely greatly magnify the net disadvantage that black applicants face, rather than mitigating it. This is because within each of these jurisdictions, job availability and overall callback rates are lower in nonwhite neighborhoods.

Other local characteristics, including partisan vote share, crime rates, income, and poverty rates, did not predict racial discrimination rates once racial composition was controlled for, nor did observable business characteristics or the other varied characteristics of our applicants. The white advantage was much larger in New Jersey than in New York City, even after accounting for neighborhood-level differences.